Andrej Karpathy's post on software 2.0 made a splash earlier this week contending that "a large portion of programmers of tomorrow do not maintain complex software repositories, write intricate programs, or analyze their running times. They collect, clean, manipulate, label, analyze and visualize data that feeds neural networks." Pete Warden expands on that point arguing that any traditional software project which after all is just data processing using explicit programming can be improved significantly by applying modern machine learning. A further interesting point is that single deep learning based model is far easier to improve than a set of deeply interconnected modules, and the maintenance becomes far easier.